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How to be a successful programmer?

programmer working

Estimated reading time: 11 minutes

Nowadays, programming is one of the most valued skills in the job market. And this is due to a simple reason: Knowing how to program allows you to create countless technological solutions. Applications, websites, games and systems are just some of the possibilities. 

But after all, how to be a programmer Of success? Is there an easier way to do well in this profession? Will the no-code platforms can they help you on this journey? 

In this content, we will show you what a programmer does and what he needs to be successful in the profession. We will also talk about how to invest in no-code programming to become a successful professional.

If you want to become a successful programmer, whether with or without code, you're in the right place.

Good reading!

What is a programmer?

First of all, you need to understand What is a programmer and what does he do in practice. It all starts with a computer program and programming language. 

The first refers to an application that performs a certain task on the computer, following a sequence of instructions written in a programming language. Language, on the other hand, is a system of symbols and rules that allows the programmer to communicate with the computer and define the program's behavior.

It seems complex at first glance, but it's no big deal. In a simplified way, the programmer is the professional who masters one or more programming languages. Using this knowledge and his own creativity, he can create the most varied programs, such as: 

  • System for controlling stock in a store;
  • Application to simulate a game of chess;
  • Music app for mobile devices. 

How to become a programmer?

Now that you understand what a programmer is and what he does in practice, you may be wondering “How to be a programmer? What I need to do?"

If you want to become a programmer, you need to follow these steps:

Discover why you want to be a programmer

The first step is to figure out why you want to be a programmer. Answer these questions honestly:

  • What is your motivation? 
  • What attracts you to the technology area? 
  • What are your professional goals? 
  • What are your personal interests?

Being clear about your purpose will help you to choose the best path to becoming a programmer, in addition to keeping you motivated and focused on your studies and projects.

Choose a programming language to learn first

Once you understand your motivations, it's time to choose a programming language to learn first. There's no point in wanting to learn everything at once.

There are hundreds of programming languages, each with its own characteristics, advantages and disadvantages. Some are easier to learn or more popular, while others are better suited for certain types of applications.

To choose a programming language to learn first, you can take into account some criteria, such as:

  • Relevance of the language for your professional objective;
  • Ease of learning the language;
  • Availability of language learning resources.

Don't worry about choosing the perfect or definitive language. The important thing is to start learning and then go deeper and diversify. You can learn more than one language throughout your career, depending on your needs and interests. 

Take online courses

Many people don't know where to look for good courses that suit their budget and routine. Our golden tip is: Don't get stuck in face-to-face teaching methods! 

There are several online courses, free or paid, that teach you from the basics to the advanced of a programming language. It is a flexible way of learning, in which you can study at your own pace, at the time and place you prefer, and count on the support of instructors and colleagues.

Here in No-Code Start-Up, you can find online programming courses without code. It is worth checking!

Watch video tutorials

If you don't yet have the financial means to purchase a complete course, know that there are many excellent and free tutorials available. Can you find free tutorials at different levels of depth on platforms such as:

  • YouTube;
  • TikTok; 
  • Websites specializing in programming. 

Read books and e-books

Another way to learn a programming language is by reading books and e-books. There are several materials that teach you concepts, rules and applications of a programming language, with theory, examples and exercises. You can find books and e-books on sites like:

  • Amazon;
  • O'Reilly;
  • Packt.

Use tools that make programming easier

In the learning process, you may come across some doubts. But there are some programming tools that can help you avoid confusion. There are many tools, such as:

See how other people program

Learning from more experienced people is always a great idea. Eventually, you will find yourself stuck, without creativity to solve problems. But don't despair!

Look for other people who may be experiencing the same problem. Two minds together always work better, right? Furthermore, you can make new friends and contacts, expanding your network. 

Searching for discussion forums about programming and technology is an excellent way to learn from the experience of other programmers.

Tips for being a successful programmer

Perhaps you who are reading this text are already a programmer, but are having difficulty finding success in the area. In that case, we need to tell you something:

Being a successful programmer doesn't just mean knowing how to program. It is essential to have other skills, attitudes and behaviors that differentiate you from others. 

We've put together some tips that can help you be more successful as a programmer. Let's go? 

Choose a language and be very good at it

As we have seen, there are several programming languages, each with its own particularities and applications. It's great to have a general idea of the most used ones, but that won't be enough. 

To stand out as a programmer, you need to master a language, even if it is codeless.. It's not enough to know the basics or intermediate of the language, you need to know the advanced, the expert, the ninja!

Understand the fundamentals of programming

Do you know the fundamentals of programming? They include:

  • Programming logic;
  • Data structures;
  • Programming paradigms;
  • Design standards.

There are still other fundamentals, but you need to master some of these. This is because understanding the fundamentals of programming is essential. They allow you to understand how programming works, how to apply the concepts in different languages and situations and how to develop clean, efficient and robust code.

Develop customized projects

Another way to stand out is to develop personalized projects. I.e, projects you create on your own that reflect your interests, ideas and passions

Developing custom projects is one of the best ways to learn and improve a programming language. Putting everything you've learned into practice, even if it's on a personal project, can give you a unique opportunity to face challenges, overcome difficulties and find solutions. 

Network

Networking means creating and maintaining a network of professional contacts who can help, support, guide and recommend you in your programming career.

This practice can be done through participation in lectures, events, communities and collaborations. It's a strategic and beneficial way to connect with people who can teach, inspire and propel you in your career.

Build a rich portfolio

This tip is perhaps one of the most important. Building a portfolio without ever landing a big project may seem impossible, but it's not. Your portfolio should contain all the projects you created or participated in, which demonstrate your skills, competencies and experiences as a programmer.

And if you haven't had any formal experience yet, create your own. Remember the tip about personalized projects? All of them can serve as a portfolio to make you stand out. Use and abuse your creativity!

How to be a successful no-code developer?

So far, we've talked about how to become and be a successful programmer, using traditional programming languages, which require you to write code to create programs. 

But did you know that there is an alternative way of programming that doesn't require you to write code? Yes, it exists and it is called no-code programming. 

Codeless programming is a trend that is gaining more and more space and popularity in the world of technology, as it democratizes access to programming. With it, anyone, with or without technical knowledge, can create applications and robust systems.

But how to be a successful no-code programming developer? Next, we'll give you some tips:

Learn the fundamentals of codeless programming

We previously commented on the importance of knowing the general principles of programming and, in the context of the no-code universe, this is no different. It is important that you understand about: 

  • workflows;
  • automation processes;
  • conditional logic, etc.

Furthermore, we suggest searching low code tools and in the code that can be used in the programming process.

Follow news

The world of technology is a constantly evolving landscape. Therefore, it is important to always be attentive and follow the news. 

New tools, platforms and techniques are being developed regularly to make the process of creating applications and systems even easier without the need to write code.

One of the most strategic ways to keep up with news is to follow people, companies, organizations and influencers who are references in the area. Try to keep them close. It’s even possible to network along the way..

Take courses 

This is the golden tip! You probably already know the importance of taking courses and investing in specialized knowledge. But did you know that here at No-Code Start-Up we offer free courses? 

Take a Bubble course for free to begin your journey as a successful no-code programmer. 

Or, if you prefer, take a FlutterFlow course completely free and learn how to develop amazing websites in no time. 

Join no-code communities

Communities always help us stay connected, exchange experiences and even find job opportunities. Finding your community of no-code programmers is easy. You can participate in forums, subscribe to newsletters and even groups on WhatsApp or Telegram. 

The important thing is to connect with other people who can inspire you and boost your career. We even have three incredible communities that you can join:

Get to know our communities and join our no-code revolution right now!

No-Code Start-Up can help you!

If you don't know us yet, nice to meet you, we are No-Code Start-Up! 

Our mission is to help democratize the programming profession.  

No-code is the future and the time is now. Come with us to surf this wave!

Discover our blog!

No-Code Start-Up

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The WhatsApp API is one of the main solutions for companies that want to scale their customer service and communication automation. 

WhatsApp, being one of the most popular messaging apps in the world, allows direct and efficient interactions with customers. However, when it comes to automation and integration, using the WhatsApp API becomes essential.

So, there are two main options for this integration: the Official WhatsApp Business API and the Unofficial APIs. But which one should you choose? 

In this article, we’ll explore the differences, advantages, disadvantages, pricing models, and costs to help you make the best decision for your project. Keep reading and find out which WhatsApp API makes the most sense for your business!

Types of WhatsApp available on the market: discover the options

types of whatsapp available in the market

Before we talk about WhatsApp APIs, it is important to understand the three main types of WhatsApp available:

Personal WhatsApp

WhatsApp Personal is the traditional version of the app, used by billions of people around the world. Intended for individual users, it does not include business-oriented features or automation.

WhatsApp BusinessVersion 

Version aimed at small and medium businesses. This version has features such as a product catalog, automatic messages and business profiles, but still relies on manual interactions. 

Furthermore, it allows the simultaneous use of two numbers on the same device, one in the personal application and the other in the Business application, in a completely legal manner and in line with Meta's guidelines.

WhatsApp Business API

Unlike previous versions, WhatsApp Business API is not an application, but a cloud-based solution that allows WhatsApp integration to different systems, enabling automation and personalization of interactions.

Companies that manage a large volume of messages use this API to optimize communication with customers, ensuring efficiency and scalability. With this solution, it is possible to:

  • automate the sending of messages and notifications;
  • to create chatbots for customer service;
  • integrate WhatsApp with CRMs, ERPs and other business platforms;
  • use artificial intelligence to personalize interactions.

How does the WhatsApp Business API work?

The WhatsApp Business API acts as a bridge between different systems, allowing softwares to communicate automatically. Since it is not an application installed on the cell phone, the entire operation takes place in the cloud, ensuring scalability and reliability for companies that need high-performance communication.

Although initially aimed at developers, today there are several solutions that simplify the implementation of the WhatsApp Business API, making it accessible to companies of different sizes.

Now that we understand the concept, let's explore the differences between the Official WhatsApp API and Unofficial WhatsApp APIs.

Official API vs. Unofficial API: Know the main differences

official api vs unofficial api differences

Businesses can choose between two types of WhatsApp API for integration:

  • Official WhatsApp Business API (provided directly by Meta or licensed companies);
  • Unofficial APIs (provided by third parties, without any connection to Meta, but within the law).

Next, we will understand the main differences between them.

Official WhatsApp Business API

The Official WhatsApp Business API is provided by Meta (Facebook) itself or by licensed companies. Meta recently began offering this service directly to end users, without the need for licensed intermediaries. 

This API can be integrated directly via Facebook's Business Manager (BM), ensuring security and compliance with Meta's policies. Among the main features of the Official API:

  • integration via Facebook Business Manager;
  • mandatory use of pre-approved message templates to start conversations;
  • billing based on conversations initiated;
  • restriction on sending messages outside of Meta's rules;
  • lower risk of blocking, as long as you follow the guidelines/

Please note that Meta does not allow unrestricted sending of messages. To start a conversation, it is mandatory to use approved message templates, ensuring that the contact complies with WhatsApp policies. The template categories are:

  • marketing: promotions, coupons and offers;
  • utility: order confirmations, delivery tracking;
  • authentication: sending verification codes;
  • service: user-initiated messages at no additional cost.

After the first template is sent, the conversation can continue normally for up to 24 hours without the need for a new template.

And how does billing work on the Official API?

The pricing for the Official WhatsApp API is based on conversations initiated and varies depending on the message category:

  • marketing messages: about R$ 0.36 per conversation started;
  • utility messages: approximately R$ 0.04 per conversation initiated;
  • authentication messages: around R$ 0.015 per conversation initiated;
  • client initiated messages: at no additional cost.

Other important points about billing include the 24-hour validity for each conversation initiated by the company, which means that if it is necessary to continue the interaction after this period, a new paid template will be required. 

Additionally, starting in April 2025, authentication and utility messages sent within this 24-hour window will no longer be charged.

Unofficial APIs

Unofficial APIs are solutions offered by third parties, with no direct relationship with Meta. Although they are not licensed, many of these APIs are completely legal and follow security standards. The main characteristics of Unofficial APIs include: 

  • simplified integration via QR Code;
  • allows sending messages without the need for pre-approved templates;
  • fixed price per integrated WhatsApp number;
  • greater flexibility for shipping and automation;
  • higher risk of ban in case of spam or inappropriate use.

Unlike the Official API, which requires template approval and follows strict rules, Unofficial APIs allow messages to be sent freely, without category restrictions or prior approval. This allows for more dynamic contact with customers, ideal for companies that need freedom in communication.

And how does the billing work? Unofficial APIs?

The pricing of Unofficial APIs varies depending on the provider. Some operate with fixed monthly plans, while others charge per connected WhatsApp number.

  • some companies offer plans starting from R$99 per integrated WhatsApp number;
  • others offer packages for multiple numbers, reducing the cost per account;
  • There are open-source options, which can be used free of charge, but require their own infrastructure.

Despite the freedom offered by Unofficial WhatsApp APIs, it is essential to consider the risks involved. Since there is no direct link to WhatsApp, these APIs are more prone to blocking, especially when used for mass sending without the proper consent of users.

Furthermore, Meta support and warranty are not available, which means that any technical issues or blockages will depend solely on the API provider.

Sending messages without the recipients' authorization can also result in restrictions, compromising the company's continued communication with its customers.

So which API to choose?

which whatsapp api to choose

Choosing between the Official WhatsApp API and Unofficial WhatsApp APIs depends on your business needs. While the Official API provides greater security and compliance, Unofficial APIs offer more freedom and predictable costs.

Evaluate your options based on your message volume, need for automation, and level of risk you are willing to take.

To learn more about automation and other efficient strategies for integrate chatbots, automatic notifications and artificial intelligence to your business, explore more at our YouTube channel and in the NoCode StartUp website.

Artificial intelligence is transforming the way we interact with technology, and AI agents are one of the most powerful advancements in this area. However, to make these agents truly effective, it’s essential to train them with data specific to your business.

In this article, we will explore how to create an AI agent using the RAG technique (Retrieval-Augmented Generation) to train models with custom information. You will learn three practical ways to implement this in your own project. 

Ready? Happy reading! 

What is an AI agent and how does it work with RAG?

What is an AI agent and how does it work?

Before we get into the practical part, it is important to understand the concept of an AI agent and how it can be improved using RAG.

Basically, an AI agent is a system that can interpret commands, process information, and generate responses autonomously. To do this, it needs three fundamental elements:

  • AI model: the agent is based on models such as GPT, Llama or Claude, responsible for interpreting and generating text based on learned patterns;
  • Base prompt: these are the instructions that define how the agent should behave and structure its responses;
  • memory: essential for AI to remember previous interactions. Some agents have both short-term and long-term memory, allowing the conversation to continue.

In addition to these features, an AI agent can be even more efficient when using the RAG (Retrieval-Augmented Generation) technique, as we mentioned earlier. This means that, instead of relying exclusively on the model's prior knowledge, it can query external databases, such as documents, PDFs, Notion pages, or spreadsheets. 

In this way, an agent trained with RAG becomes an expert in specific content, ensuring more precise and contextualized responses.

Method 1: Creating an agent with Dify

method 1 creating an agent with dify

Now that you understand the basics, let's get to the practical part: how to create an AI agent trained with your own data!

One of the easiest and most effective ways to create a RAG-trained agent is by using Difyi. This tool allows you to integrate knowledge bases into your assistant quickly and intuitively.

To train your agent at Dify, follow the step by step below:

  • access the “Knowledge Base” tab within the Dify platform;
  • upload your documents, such as PDFs, HTML files, spreadsheets or web pages;
  • Dify processes the files and transforms them into numeric vectors, converting the textual content into a format that AI can interpret efficiently.

This process is known as embedding, in which the tool structures the data on a vector basis, allowing the AI to search and retrieve the most relevant information whenever a question is asked.

Additionally, Dify makes it easy to create virtual databases by organizing knowledge into chunks of information. This way, when a user asks the agent a question, the agent quickly identifies which chunk of text best fits the desired answer.

With Difyi, you can create specialized agents for different purposes, such as:

  • customer support assistants, who access FAQs and technical manuals;
  • customer service chatbots, which answer questions about products and services;
  • sales agents, which use strategic information to personalize approaches.

The best part? Dify automates this entire process behind the scenes, making implementation simple and practical.

Method 2: Creating an agent with OpenAI Assistants and RAG

method 2 creating an agent with openai assistants

Another efficient way to train an AI agent with RAG is to use OpenAI Assistants. This solution allows you to create custom assistants, define specific behaviors, and incorporate documents so that the AI can query and respond accurately.

Unlike Dify, which automates much of the process, OpenAI offers greater control over the agent’s settings. To create your assistant using this tool, follow the steps below:

  • access the OpenAI platform and go to the “Assistants” tab;
  • create a new wizard, defining a name, description and specific instructions;
  • choose an AI model, such as GPT-4 Turbo, to ensure more complete and contextual answers;
  • Upload files that he will use as reference, such as technical manuals, internal documents, or knowledge bases.

When documents are added to the platform, OpenAI transforms this content into a vector database. This way, the agent can consult the information whenever necessary, without relying solely on the model's pre-trained knowledge. 

This allows it to provide more personalized and up-to-date responses without requiring a complete AI re-processing. Additionally, OpenAI manages all the infrastructure needed to store and retrieve this information, making it easy to implement for those who don’t want to set up their own database.

One of the main advantages of this approach is its ease of implementation, as OpenAI takes care of the technical part, making the process simple and intuitive. In addition, the model guarantees high accuracy, combining the power of GPT-4 Turbo with specific information about your business, making the assistant much more effective. 

If your goal is to create a specialized AI agent without having to set up an advanced technical environment, OpenAI Assistants can be a great choice.

Method 3: Creating an agent with N8N and Supabase

method 3 creating an agent with n8n and supabase

The third way to create an AI agent trained with RAG is by using the integration between N8N and Supabase. This approach allows greater control over the data and optimizes the search for relevant information within the vector database.

While tools like Dify and OpenAI Assistants simplify the process, using N8N in conjunction with Supabase offers more versatility and reduces operational costs by allowing the framework to be fully configured and managed within your own environment.

To create an AI agent trained with this combination, follow the steps below:

  • configure the vector database in supabase to store the reference documents;
  • upload the files that the agent will use as a knowledge base, such as manuals, FAQs or technical ebooks;
  • integrate Supabase with N8N to enable AI to query data and provide contextualized answers;
  • develop automated flows in N8N to structure agent interactions with users;
  • optimize agent responses by ensuring that they can access the most relevant blocks of information within the database.

But why use N8N and Supabase? with RAG?

Unlike other solutions, this approach allows for an advanced level of customization and control over the vector database. When a user asks the agent a question, it fetches the most relevant vector of data from Supabase, ensuring that the answer is based on the stored documents.

Additionally, N8N allows you to connect the AI agent to different applications, such as Whatsapp, Slack and Google Drive, expanding the possibilities of use and automation. This flexibility makes the model ideal for companies that need a highly specialized agent.

Among the main advantages of this implementation, the following stand out:

  • greater control over datas, allowing adjustments and customizations as needed;
  • cost reduction, as Supabase replaces paid solutions for vector storage;
  • advanced automation, with intelligent flows and integrations in N8N;
  • scalability, allowing the knowledge base to grow according to business needs;
  • greater efficiency, as the agent accesses information directly from the vector database, without relying solely on the AI model.

If you are looking for flexibility and cost reduction, N8N + Supabase is a powerful solution for training specialized AI agents with RAG.

Conclusion

Training an AI agent with your own data is an essential strategy for obtaining more accurate responses aligned with the context of your business. With RAG, you can transform internal files and documents into structured knowledge for AI, optimizing processes and improving the user experience.

If you want to dive deeper into the topic and learn how to create your own AI agents, check out the complete N8N course at NoCode Startup and take your automation to the next level!

Imagine you have a super-intelligent assistant trained based on all the knowledge available on the internet. However, when it comes to information specific to your business, it may not have direct references. So, how do you overcome this limitation?

One of the most effective ways to improve your assistant's intelligence is to train it with custom data, such as documents, articles, and internal files. 

This technique is known as RAG (Retrieval-Augmented Generation) and allows AI assistants to combine pre-existing knowledge with specific information to provide more accurate and useful answers.

Continue reading to better understand how this approach can transform the use of AI in your business.

How does RAG (Retrieval-Augmented Generation) work?

How does RAG work?

Now that we understand the concept of RAG (Retrieval-Augmented Generation), let's explore how it works in detail. 

Unlike traditional AI assistants that simply generate answers based on previously trained knowledge, RAG searches for information from external sources and combines that data with its prior knowledge to provide more accurate and relevant answers. 

The process can be divided into three main steps:

Ask the AI model

The user asks the AI assistant a question, just as they would in ChatGPT or another traditional chatbot.

Information Search (Retrieval)

The AI assistant queries a specific database, such as PDFs, websites, internal documents, or a business knowledge base. It retrieves the most relevant information to answer the question.

Augmented Generation

With the data retrieved, AI refines and structures the response by combining information from the knowledge base with its own linguistic model. This ensures a contextualized, accurate and relevant response.

This method is highly efficient as it allows AI to provide more personalized responses based on internal data. Additionally, the technology can leverage product documentation, support knowledge bases, and even company policies to ensure accurate and relevant information.

how does rag generation increase work

However, unlike a conventional chatbot, which responds based only on its original training, a RAG model can be constantly updated with new information, without the need for massive retraining.

In other words, this allows the AI to be highly dynamic and evolve progressively as new content is added, ensuring greater accuracy and relevance in responses.

For example, within the NoCode community, we provide assistants that use RAG to answer questions about tools such as make up, Diff, N8N and Bubble.

Furthermore, these assistants have been trained with specific documentation for these platforms, which allows them to provide even more detailed and accurate answers to students, thus facilitating learning and resolving technical queries.

5 Benefits of using RAG

Benefits of using RAG

Now that you understand how RAG works, let's explore the main benefits that this technology can bring to companies and users:

1. More accurate and contextualized responses

RAG enables AI assistants to query up-to-date information in real time, making responses more relevant and detailed.

2. Automation and efficiency

With the ability to access specific knowledge bases, AI reduces the need for constant human support, optimizing time and resources.

3. Continuous learning without the need for retraining

Unlike traditional AI models, which need to be constantly trained and retrained to learn new information, RAG can simply query updated databases.

4. Customization for different businesses

Companies can tailor AI to answer industry-specific questions by training the assistant with technical manuals, internal knowledge bases, and other relevant documents.

5. Applying RAG in customer support

In addition to academic and educational use, companies across a variety of sectors are using RAG to improve customer support.

Imagine a technology company that sells complex softwares. Customers frequently contact support with questions about specific features. 

With an AI assistant trained with RAG, a company can feed the AI with its internal knowledge base, technical manuals, and FAQs. This allows the agent to answer questions accurately and quickly, helping to reduce the need for human intervention and streamline customer support.

How to apply RAG in your business?

Companies from different segments can take advantage of this technology to improve internal processes, customer service and task automation. Below, check out some practical strategies for applying RAG to your business.

1. Identify your company's main needs

Before integrating RAG, evaluate which areas of your business can benefit from this technology. Ask yourself the following questions: 

  • Does customer support receive a lot of repetitive questions?
  • Does your team need to access technical documents frequently?
  • Is there a large database that could be better utilized?
  • Could internal training be optimized with an AI assistant?

2. Choose the right data sources

The great advantage of RAG is its ability to search for information from external sources. To ensure accurate and reliable answers, it is essential to select the best data repositories. Some options include:

  • technical documentation and product manuals;
  • FAQs and internal knowledge bases;
  • articles, research and case studies;
  • structured data from CRMS and ERPS;
  • pdf files, spreadsheets and notion.

3. Integrate RAG with your existing tools

For best results, RAG should be connected to the platforms your team already uses. Some ways to integrate include:

  • Chatbots and virtual assistants: AI trained to answer recurring questions and provide technical support;
  • Management systems (CRM/ERP): AI can access customer data to provide more personalized responses;
  • E-learning and corporate training: intelligent assistants that help employees access learning materials quickly;
  • E-commerce and customer service: chatbots that check inventory, return policies and product recommendations.

4. Evaluate and optimize 

Implementing RAG doesn’t end with the initial setup. It’s essential to monitor AI performance by analyzing metrics such as:

  • response accuracy rate;
  • user satisfaction;
  • reduction of service time;
  • most frequently asked questions and opportunities for improvement.

With this information, you can improve the AI database and ensure that the answers become increasingly accurate.

Conclusion

Whether it’s to improve customer support, automate processes or optimize internal knowledge management, RAG is a powerful and affordable solution for companies in different segments. 

With this technology, AI agents can access specific knowledge bases, improve the user experience and reduce the need for extensive training.

If you want to learn how to create intelligent AI assistants using N8N, check out NoCode Startup's complete course. In it, you will have access to practical training on automation and data integration to make your business' AI even more efficient.

Explore more about the N8N Course – NoCode Startup and start transforming your company with artificial intelligence! 

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